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Article
Publication date: 27 September 2011

Takeaki Kariya, Fumiaki Ushiyama and Stanley R. Pliska

The purpose of this paper is to generalize the one‐factor mortgage‐backed securities (MBS)‐pricing model proposed by Kariya and Kobayashi to a three‐factor model. The…

Abstract

Purpose

The purpose of this paper is to generalize the one‐factor mortgage‐backed securities (MBS)‐pricing model proposed by Kariya and Kobayashi to a three‐factor model. The authors describe prepayment behavior due to refinancing and rising housing prices by discretetime, no‐arbitrage pricing theory, making an association between prepayment behavior and cash flow patterns.

Design/methodology/approach

The structure, rationality and potential for practical use of our model is demonstrated by valuing an MBS via Monte Carlo simulation and then conducting a comparative static analysis.

Findings

The proposed model is found to be effective for analysing MBS cash flow patterns, making a decision for bond investments and risk management due to prepayment.

Originality/value

While the one‐factor valuation model Kariya and Kobayashi treated is a basic framework, the generalized model presented in this paper is much more effective for analysing MBS cash flow patterns, making a decision for bond investments and risk management due to prepayment.

Article
Publication date: 1 February 2019

Zhiwu Hong, Linlin Niu and Gengming Zeng

Using a discrete-time version of the arbitrage-free Nelson–Siegel (AFNS) term structure model, the authors examine how yield curves in the US and China react to exchange…

Abstract

Purpose

Using a discrete-time version of the arbitrage-free Nelson–Siegel (AFNS) term structure model, the authors examine how yield curves in the US and China react to exchange rate policy shocks as China introduces gradual reforms to make its exchange rate regime more flexible. The paper aims to discuss this issue.

Design/methodology/approach

The authors characterize the specification of the discrete-time AFNS model, prove the uniqueness of the solution for model identification, perform specification analysis on its canonical form and detail the MCMC estimation method with a fast and reliable prior extraction step.

Findings

Model decomposition reveals that in the US yield responses, changes in risk premia for medium- to long-term yields dominate changes in yield expectation for short- to medium-term yields, indicating that the portfolio rebalancing effect due to varying risk perception is stronger than the signaling effect due to policy rate expectation.

Practical implications

The results are helpful in diagnosing market sentiment and exchange rate risk pricing as China further internationalizes its currency.

Originality/value

The methodology can be easily extended to study yield curve responses to other scenarios of policy shocks or regime changes.

Details

China Finance Review International, vol. 9 no. 3
Type: Research Article
ISSN: 2044-1398

Keywords

Article
Publication date: 27 February 2009

Anyssa Trimech, Hedi Kortas, Salwa Benammou and Samir Benammou

The purpose of this paper is to discuss a multiscale pricing model for the French stock market by combining wavelet analysis and Fama‐French three‐factor model. The…

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Abstract

Purpose

The purpose of this paper is to discuss a multiscale pricing model for the French stock market by combining wavelet analysis and Fama‐French three‐factor model. The objective is to examine the relationship between stock returns and Fama‐French risk factors at different time‐scales.

Design/methodology/approach

Exploiting the scale separation property inherent to the maximal overlap discrete wavelet transform, the data set are decomposed into components associated with different time‐scales. This wavelet‐based decomposition scheme allows the three Fama‐French models to be tested over different investments periods.

Findings

The obtained results show that the explanatory power of the Fama‐French three‐factor model becomes stronger as the wavelet scale increases. Besides, the relationship between the portfolio returns and the risk factors (i.e. the market, size and value factors) depends significantly upon the considered time‐horizon.

Practical implications

The proposed methodology offers investors the opportunity to construct dynamic portfolio management strategies by taking into account the multiscale nature of risk and return. Moreover, it gives a new insight to fund rating and fund selection issues in relation to heterogeneous investments periods.

Originality/value

The paper uses wavelets as a relatively new and powerful tool for statistical analysis that allows a new understanding of pricing models. The paper will be of interest not only for academics in the field of asset pricing but also for fund managers and financial market investors.

Details

The Journal of Risk Finance, vol. 10 no. 2
Type: Research Article
ISSN: 1526-5943

Keywords

Book part
Publication date: 11 December 2006

Wayne Ferson, Darren Kisgen and Tyler Henry

We evaluate the performance of fixed income mutual funds using stochastic discount factors motivated by continuous-time term structure models. Time-aggregation of these…

Abstract

We evaluate the performance of fixed income mutual funds using stochastic discount factors motivated by continuous-time term structure models. Time-aggregation of these models for discrete returns generates new empirical “factors,” and these factors contribute significant explanatory power to the models. We provide a conditional performance evaluation for US fixed income mutual funds, conditioning on a variety of discrete ex-ante characterizations of the states of the economy. During 1985–1999 we find that fixed income funds return less on average than passive benchmarks that do not pay expenses, but not in all economic states. Fixed income funds typically do poorly when short-term interest rates or industrial capacity utilization rates are high, and offer higher returns when quality-related credit spreads are high. We find more heterogeneity across fund styles than across characteristics-based fund groups. Mortgage funds underperform a GNMA index in all economic states. These excess returns are reduced, and typically become insignificant, when we adjust for risk using the models.

Details

Research in Finance
Type: Book
ISBN: 978-1-84950-441-6

Article
Publication date: 27 September 2011

Robert J. Elliott, Tak Kuen Siu and Alex Badescu

The purpose of this paper is to consider a discretetime, Markov, regime‐switching, affine term‐structure model for valuing bonds and other interest rate securities. The…

Abstract

Purpose

The purpose of this paper is to consider a discretetime, Markov, regime‐switching, affine term‐structure model for valuing bonds and other interest rate securities. The proposed model incorporates the impact of structural changes in (macro)‐economic conditions on interest‐rate dynamics. The market in the proposed model is, in general, incomplete. A modified version of the Esscher transform, namely, a double Esscher transform, is used to specify a price kernel so that both market and economic risks are taken into account.

Design/methodology/approach

The market in the proposed model is, in general, incomplete. A modified version of the Esscher transform, namely, a double Esscher transform, is used to specify a price kernel so that both market and economic risks are taken into account.

Findings

The authors derive a simple way to give exponential affine forms of bond prices using backward induction. The authors also consider a continuous‐time extension of the model and derive exponential affine forms of bond prices using the concept of stochastic flows.

Originality/value

The methods and results presented in the paper are new.

Book part
Publication date: 24 October 2013

Panagiotis Dontis-Charitos, Orla Gough, K. Ben Nowman and Sheeja Sivaprasad

We investigate the return and volatility spillovers from major UK banks to Financial Times Stock Exchange 100 (FTSE 100) index using Gaussian estimation and continuous time

Abstract

We investigate the return and volatility spillovers from major UK banks to Financial Times Stock Exchange 100 (FTSE 100) index using Gaussian estimation and continuous time models as well as discrete time multivariate GARCH (MGARCH) modelling approaches. Using daily, weekly and monthly data over the period December 1999–December 2010, which includes the recent 2007–2009 global financial crisis, empirical estimates of uni- and/or bi-directional return and volatility spillovers are provided. The bivariate MGARCH results reveal strong return spillovers from the FTSE to the banks, and no return spillover from the latter to the FTSE. Nevertheless, strong bi-directional volatility transmission is verified. The continuous time analysis provides mixed evidence of feedback effects over the different models.

Details

Global Banking, Financial Markets and Crises
Type: Book
ISBN: 978-1-78350-170-0

Keywords

Book part
Publication date: 30 November 2011

Massimo Guidolin

I survey applications of Markov switching models to the asset pricing and portfolio choice literatures. In particular, I discuss the potential that Markov switching models

Abstract

I survey applications of Markov switching models to the asset pricing and portfolio choice literatures. In particular, I discuss the potential that Markov switching models have to fit financial time series and at the same time provide powerful tools to test hypotheses formulated in the light of financial theories, and to generate positive economic value, as measured by risk-adjusted performances, in dynamic asset allocation applications. The chapter also reviews the role of Markov switching dynamics in modern asset pricing models in which the no-arbitrage principle is used to characterize the properties of the fundamental pricing measure in the presence of regimes.

Details

Missing Data Methods: Time-Series Methods and Applications
Type: Book
ISBN: 978-1-78052-526-6

Keywords

Article
Publication date: 27 May 2022

John Galakis, Ioannis Vrontos and Panos Xidonas

This study aims to introduce a tree-structured linear and quantile regression framework to the analysis and modeling of equity returns, within the context of asset pricing.

Abstract

Purpose

This study aims to introduce a tree-structured linear and quantile regression framework to the analysis and modeling of equity returns, within the context of asset pricing.

Design/Methodology/Approach

The approach is based on the idea of a binary tree, where every terminal node parameterizes a local regression model for a specific partition of the data. A Bayesian stochastic method is developed including model selection and estimation of the tree structure parameters. The framework is applied on numerous U.S. asset pricing models, using alternative mimicking factor portfolios, frequency of data, market indices, and equity portfolios.

Findings

The findings reveal strong evidence that asset returns exhibit asymmetric effects and non- linear patterns to different common factors, but, more importantly, that there are multiple thresholds that create several partitions in the common factor space.

Originality/Value

To the best of the authors' knowledge, this paper is the first to explore and apply a tree-structured and quantile regression framework in an asset pricing context.

Details

Review of Accounting and Finance, vol. 21 no. 3
Type: Research Article
ISSN: 1475-7702

Keywords

Article
Publication date: 11 March 2022

Zhai Longzhen and ShaoHong Feng

The rapid evacuation of personnel in emergency situations is of great significance to the safety of pedestrians. In order to further improve the evacuation efficiency in…

Abstract

Purpose

The rapid evacuation of personnel in emergency situations is of great significance to the safety of pedestrians. In order to further improve the evacuation efficiency in emergency situations, this paper proposes a pedestrian evacuation model based on improved cellular automata based on microscopic features.

Design/methodology/approach

First, the space is divided into finer grids, so that a single pedestrian occupies multiple grids to show the microscopic behavior between pedestrians. Second, to simulate the velocity of pedestrian movement under different personnel density, a dynamic grid velocity model is designed to establish a linear correspondence relationship with the density of people in the surrounding environment. Finally, the pedestrian dynamic exit selection mechanism is established to simulate the pedestrian dynamic exit selection process.

Findings

The proposed method is applied to single-exit space evacuation, multi-exit space evacuation, and space evacuation with obstacles, respectively. Average speed and personnel evacuation decisions are analyzed in specific applications. The method proposed in this paper can provide the optimal evacuation plan for pedestrians in multiple exit and obstacle environments.

Practical implications/Social implications

In fire and emergency situations, the method proposed in this paper can provide a more effective evacuation strategy for pedestrians. The method proposed in this paper can quickly get pedestrians out of the dangerous area and provide a certain reference value for the stable development of society.

Originality/value

This paper proposes a cellular automata pedestrian evacuation method based on a fine grid velocity model. This method can more realistically simulate the microscopic behavior of pedestrians. The proposed model increases the speed of pedestrian movement, allowing pedestrians to dynamically adjust the speed according to the specific situation.

Details

Engineering, Construction and Architectural Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0969-9988

Keywords

Article
Publication date: 14 December 2017

Vinod K.T., S. Prabagaran and O.A. Joseph

The purpose of this paper is to determine the interaction between dynamic due date assignment methods and scheduling decision rules in a typical dynamic job shop…

Abstract

Purpose

The purpose of this paper is to determine the interaction between dynamic due date assignment methods and scheduling decision rules in a typical dynamic job shop production system in which setup times are sequence dependent. Two due date assignment methods and six scheduling rules are considered for detailed investigation. The scheduling rules include two new rules which are modifications of the existing rules. The performance of the job shop system is evaluated using various measures related to flow time and tardiness.

Design/methodology/approach

A discrete-event simulation model is developed to describe the operation of the job shop. The simulation results are subjected to statistical analysis based on the method of analysis of variance. Regression-based analytical models have been developed using the simulation results. Since the due date assignment methods and the scheduling rules are qualitative in nature, they are modeled using dummy variables. The validation of the regression models involves comparing the predictions of the performance measures of the system with the results obtained through simulation.

Findings

The proposed scheduling rules provide better performance for the mean tardiness measure under both the due date assignment methods. The regression models yield a good prediction of the performance of the job shop.

Research limitations/implications

Other methods of due date assignment can also be considered. There is a need for further research to investigate the performance of due date assignment methods and scheduling rules for the experimental conditions that involve system disruptions, namely, breakdowns of machines.

Practical implications

The explicit consideration of sequence-dependent setup time (SDST) certainly enhances the performance of the system. With appropriate combination of due date assignment methods and scheduling rules, better performance of the system can be obtained under different shop floor conditions characterized by setup time and arrival rate of jobs. With reductions in mean flow time and mean tardiness, customers are benefitted in terms of timely delivery promises, thus leading to improved service level of the firm. Reductions in manufacturing lead time can generate numerous other benefits, including lower inventory levels, improved quality, lower costs, and lesser forecasting error.

Originality/value

Two modified scheduling rules for scheduling a dynamic job shop with SDST are proposed. The analysis of the dynamic due date assignment methods in a dynamic job shop with SDST is a significant contribution of the present study. The development of regression-based analytical models for a dynamic job shop operating in an SDST environment is a novelty of the present study.

Details

Journal of Manufacturing Technology Management, vol. 30 no. 6
Type: Research Article
ISSN: 1741-038X

Keywords

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